The purpose of this paper is to discuss the role of standardised Chart of Accounts (CoA) in public sector accounting and reporting, particularly focusing matters concerning the importance and need to have a CoA at national level, the issues needed to be taken into account when developing a CoA, and the expected impact of using a CoA as a bookkeeping instrument on the accuracy of accounting records and ultimately on the reliability of the financial information.
Based on documentary analysis and on a survey to some of those involved in the development of a CoA for public sector accounting, the research uses a comparative-international perspective to learn from some national experiences and from European and international standard-setters’ perspectives, which can be considered by other countries intending to develop a CoA.
Main findings show that the link of the national CoA to National Accounts is important in countries like those from EU, where a common fiscal discipline is monitored using these figures.
It is generally acknowledged, including by international standard-setters, that a CoA in public sector accounting is important for a need to support standardised records and accounting, and the preparation of financial statements, including consolidated and WGA.
All in all, this paper suggests that harmonising CoA within countries makes sense and the development at national level should consider specificities of public sector transactions, the link to the financial statements items, and the link to the budget as most important issues.

This paper explores the organizing elements that foster emergent collaboration within large-scale communities on online social platforms like Twitter. This study is based on a case study of the #BlackLivesMatter social movement and draws on organizing dynamics and online social network literature, combined with the analysis of 2050 tweets collected from days where the movement had high levels of activity. Drawing on the literature review, we propose a framework consisting of three organizing elements: structure, engagement, and communicative content that are essential in analyzing online collaboration. This paper uses this framework to analyze the collected tweets and identify how actors organize and engage in large-scale communities founded by emergent online collaboration. This paper identifies characteristics of how these key elements and a dynamic interplay between the two logics of action foster emergent collaboration in social movements using Twitter.

The artificial intelligence (AI) field can be traced back to the 1950th (Tzafestas, 2016). In recent years, with
the emerging of web 3.0 and big data, AI is rapidly flourishing and start to be widely used in many fields,
such as high tech, the automotive industry, financial services, retail, media, education, healthcare and
travel (Chui, 2017). Early business adopters regard AI as increasing revenue, while organizations using AI
expect lower costs and efficient service (Chui, 2017). In the healthcare sector, the use of AI is slow,
compared with other fields, but its adoption is steadily increasing, due to the nature of healthcare
services, which require face-to-face interactions for its service delivery (Jung & Padman, 2015). The use of
AI in healthcare is a promising field for many businesses (Chui, 2017; Dirican, 2015; McKinsey Global
Institute, 2017) and it will be likely to redesign the healthcare sector in many aspects, such as in mining
medical records, designing treatment plans, and assisting repetitive jobs (Meskó, 2016).
In China, many public hospitals have started to use AI for providing better treatment plans and for
helping doctors in advanced decision-making for diagnoses and treatments (Christine Douglass, 2016).
The Chinese government has started introducing a number of innovation policies in order to accelerate
the development of AI, to inspire healthcare innovation, and to provide easier access to improved and
more efficient care for patients. According to Lundvall and Borrás (2006), “innovation policy covers a
wide range of initiatives and it is necessary to give some structure to the complex reality”. These
innovation policies introduced by diverse actors target both ICT firms and hospitals, with diverse policy
instruments and policy goals.
Healthcare is one of the major areas in which the government plays a central role, especially in China. AI
adoption in healthcare has a strong requirement on policy support. Existing research falls short of
analyzing the impacts of innovation policies of AI in healthcare. As a result, there is a need for both
researchers and practitioners in the public healthcare sector to understand the effects of policies on the
adoption of AI in healthcare in China. Therefore, in our study we would like to tackle the following
overarching research question: How do government innovation policies affect the use of AI by actors in
the public healthcare ecosystem? This research question is articulated in two sub-research questions:
What are the characteristics of government innovation policies (RQ1); and How do the characteristics of
government innovation policies affect the use of AI in the public healthcare ecosystem by key actors
(hospital managers, IT firms, and doctors)? (RQ2).
This extended abstract reports on the initial phases of a study aimed at answering the overarching
research question, which is part of the doctoral research design of one of the authors. Our preliminary
findings tackle RQ1 by mapping the innovation policies introduced by the government in China, with the
future goal of tackling RQ2 by investigating the effects of these policies on the use of AI by specific actors
in the public healthcare ecosystem (hospital managers, IT firms, and doctors).

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In this paper we study novice programmers’ strategies during different phases of programming. Programming strategies are about cognitive processes that result in the programmers’ code being written from scratch, edited or deleted. The paper presents a questionnaire, which will be used to investigate how and when novice programmers use different strategies and how this affects the quality of the resulting program. We identify the cognitive processes that novice programmers utilise to complete a programming task. These cognitive processes may or may not result in immediate changes in the code. The ultimate purpose of this ongoing research is to contribute to improve the initial programmer education.

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The Commensuration of Sustainability Reporting and the Crowding out of Morality

van Bommel, Koen; Rasche, Andreas; Spicer, André(Frederiksberg, 2018)

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Abstract:

Drawing on extensive case study evidence, this study unpacks sustainability reporting’s evolution from a moral values-based practice towards a financialized value-based one. We argue that this transition can be seen as a commensuration project and we examine the dynamics of this process. We find that increased levels of commensuration have moved sustainability reporting away from a focus on moral responsibility (i.e. ‘doing the right thing’) to a focus on strategic value creation for the firm. We theorize this crowding out of morality as a process of amoralization supported by the rigid cognitive framing of social and environmental issues (objectification) and the monetized coordination of relevant social interactions (marketization). We outline implications of our analysis for the scholarly debate on sustainability reporting and commensuration.

Sluice resolution in English is the problem
of finding antecedents of wh-fronted ellipses.
Previous work has relied on handcrafted
features over syntax trees that scale
poorly to other languages and domains;
in particular, to dialogue, which is one of
the most interesting applications of sluice
resolution. Syntactic information is arguably
important for sluice resolution, but
we show that multi-task learning with partial
parsing as auxiliary tasks effectively
closes the gap and buys us an additional
9% error reduction over previous work.
Since we are not directly relying on features
from partial parsers, our system is
more robust to domain shifts, giving a
26% error reduction on embedded sluices
in dialogue.

Purpose – The purpose of this paper is to examine the links between employee attitudes, customer loyalty and business results.
Methodology/approach – From a conceptual point of view, this employee-customer-business results chain is well founded and generally accepted, also in the European Excellence Model. But for many companies, it seems difficult to demonstrate such links, and several issues must be addressed to uncover the links. To investigate these links empirically, a hotel chain provided data matching employee and customer measures with measures of profit, and a modeling approach is developed.
Findings – The model is successfully applied. As it is possible to estimate and test the links, we have demonstrated the effects of employee attitudes on customer loyalty and further on business results. The findings provide strong empirical evidence for the developed model, and the study provided evidence of theemployee-customer-business result chain.
Research limitations – The study is limited to four hotels in Copenhagen, Denmark.
Practical implications – The research findings provide a better understanding of the employee-customer-business result chain and may help practitioners in improving company financial performance.
Originality/value – This paper provides new insights into the relationships between employee attitudes, customer loyalty, and business results.

Crowdsourcing is an emergent interdisciplinary theory and methodology, which in recent years has become widely diffused, raising significant questions in the innovation management literature concerning the adoption of crowdsourcing as an open innovation practice. Building on seminal research on open innovation adoption in large organizations (Chesbrough and Brunswicker, 2013; 2014), the current study presents qualitative findings on the innovation practices and strategies of incumbent firms transitioning from traditional innovation to crowdsourcing for open innovation. We discuss the impact of crowdsourcing technologies and methodologies on 1) the innovation processes, 2) the innovation content and 3) the overall scope of innovation to discover different stages of maturity in the innovation governance structures of incumbent firms (Deschamps & Nelson, 2014). Our study thus contributes to research on the firm side of crowdsourcing, providing much needed insights into the processes, procedures and structures that support the implementation of crowdsourcing for open innovation (Lüttgens et al., 2014).

Newspapers need to attract readers with headlines, anticipating their readers’ preferences. These preferences rely on topical, structural, and lexical factors. We model each of these factors in a multi-task GRU network to predict headline popularity. We find that pre-trained word embeddings provide significant improvements over untrained embeddings, as do the combination of two auxiliary tasks, newssection prediction and part-of-speech tagging. However, we also find that performance is very similar to that of a simple Logistic Regression model over character n-grams. Feature analysis reveals structural patterns of headline popularity, including the use of forward-looking deictic expressions and second person pronouns.

Sluicing resolution is the task of identifying the antecedent to a question ellipsis. Antecedents are often sentential constituents, and previous work has therefore relied on syntactic parsing, together with complex linguistic features. A recent model instead used partial parsing as an auxiliary task in sequential neural network architectures to inject syntactic information. We explore the linguistic information being brought to bear by such networks, both by defining subsets of the data exhibiting relevant linguistic characteristics, and by examining the internal representations of the network. Both perspectives provide evidence for substantial linguistic knowledge being deployed by the neural networks.

This study analyzes which firms leave multi-stakeholder initiatives (MSIs) for corporate social responsibility (CSR). Based on an analysis of all active and delisted participants from the UN Global Compact between 2000 and 2015 (n= 15,853), we find that SMEs are more likely to be delisted than larger and publicly-traded firms; that early adopters face a higher risk of being delisted; and that the presence of a local network in a country reduces the likelihood of being delisted. Based on this, we extend resource dependence theory in the context of CSR by theorizing (a) the effect of participant heterogeneity on resource dependence relationships and (b) the role of indirect influence pathways where stakeholders work through allies to manipulate the flow of resources to a firm.

This paper examines the legitimacy attached to different types of multi-stakeholder data partnerships occurring in the context of sustainable development. We develop a framework to assess the democratic legitimacy of two types of data partnerships: open data partnerships (where data and insights are mainly freely available) and closed data partnerships (where data and insights are mainly shared within a network of organizations). Our framework specifies criteria for assessing the legitimacy of relevant partnerships with regard to their input legitimacy as well as their output legitimacy. We demonstrate which particular characteristics of open and closed partnerships can be expected to influence an analysis of their input and output legitimacy.

This study presents a validated recommendation on how to shorten the surveys while still obtaining segmentation-based insights that are consistent with the analysis of the full length version of the same survey. We use latent class analysis to cluster respondents based on their responses to a survey on human values. We first define the clustering performance based on stability and similarity measures for ten random subsamples relative to the complete set. We find foremost that the use of true binary scale can potentially reduce survey completion time while still providing sufficient response information to derive clusters with characteristics that resemble those obtained with the full Likert scale version. The main motivation for this study is to provide a baseline performance of a standard clustering tool for cases when it is preferable or necessary to limit survey scope, in consideration of issues like respondent fatigue or resource constraints.

Contemporary studies must address the challenges of responding to abrupt events in highly dynamic and complex environments. We argue that decision structures and information processing capabilities enhance the ability of organizations and societies to respond effectively to the changing conditions for durable advantages. Sustainable performance arguably derives from interactive decision-making processes that deal with opportunities as they emerge informed by updated environmental analytics. The combination of experiential insights from decentralized responses and forward-looking reasoning at the center identifies a dynamic adaptive system of interacting fast and slow processes. The fast information processing observes local environmental stimuli whereas the slow information processing interprets these events and reasons about future developments. When the fast and slow processes interact they form a dynamic system that allows an organization or society to adapt gradually to the turbulent conditions. We apply the model of fast-slow interactions in organizations and societies as the key driver of sustainable adaptation.

Contemporary approaches to the study of design teams tend to assume that teamwork is entirely social, thereby failing to examine the extent to which design team processes involve the assumed joint attention and social collaboration. Nowadays mobile devices enable a situation where almost the entire design process is carried out in a team co-located setting, which allows for both individual and social creative processes during teamwork. In this perspective, this article explores the oscillation between co-located individual and social design activity. To study the shift from individual to social activity within design teamwork, we surveyed 23 hours of team activity amongst 25 high-school students by coding and analyzing captured video of their teamwork while working in a self-imposed manner on a design task. We found that different creative sub-processes, such as information search, problem defining, idea generation, decision-making, and feedback, foster different degrees of joint attention, and that the joint attention may be established more successfully through analogue and shared digital communicative resources.

Recent years have seen a surge in the use of blockchain technologies, not least because of the increased use of cryptocurrencies such as Bitcoin which rely on it. While some of the generated interest can be dismissed as hype, there is little doubt that blockchain is a technology with the potential to revolutionise certain areas of law. A careful reader following the trends would have noticed that Maersk, the Danish business conglomerate, was involved with no less than three deals revolving, in one way or another, around blockchain technology Such news should intrigue the reader since adoption of experimental methods or newest IT technologies does not normally characterise the inert maritime and transport industries. We will in this short piece give an overview of the relevance of blockchain and briefly look at three different deals which Maersk concluded around the technology. We will then give an outline of potential legal problems which these and similar deals might bring. Our preliminary conclusion is that blockchain technology - in some instances at least - has the potential to disrupt the role law traditionally plays in negotiating and executing international contracts.

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The phenomenon of financialization has received increasing attention, especially following the global financial crisis. We broaden the scope of research on financialization by investigating Open Banking initiatives. Such initiatives aim to enhance the banks’ ability to personalise cus-tomer experiences. Consumers and businesses can now easily share their data with banks and third parties to manage personal accounts and compare banking services. Such initiatives raise important questions regarding the future role of banks as well challenges and opportunities inherent in the new Open Banking landscape. We empirically investigate five Open Banking initiatives through twenty-five interviews conducted with users of Open Banking APIs as well as those managing the various initiatives. From these interviews, we develop a taxonomy and identify four open banking roles: integrator, producer, distributor, and platform. A further con-tribution is made by identifying related challenges and opportunities faced by fintechs and in-cumbents in the shifting landscape of retail banking. The challenges identified include risk of disintermediation, loss of reputation and transformational failure while the opportunities iden-tified include enhanced service innovation and risk mitigation. Overall, the study provides first insights into how the retail banking industry will adapt to new service innovations and in-creased collaboration with third party fintechs.

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Management Education has been receiving its fair share of critique, especially since the financial crisis and other business scandals that have unveiled the immoral and unethical dispositions in the business world. Questions about what kind of responsibility is being taught in business schools, if at all, have been raised, and in which way are these values being learned? In the more subtle field of learning responsibility, relationships between people, and fundamentally, the perception of 'the other', learning through theories and concepts is not sufficient. It requires rather a practice of 'unlearning' habits that have been formed through one's experience. This is where transformative learning offers a huge opportunity in management education, and the following paper explains how this kind of learning can be beneficial for future business leaders.